Predicting graduate student Performance - A case study

Graduate admission has become critical for quality assurance. An innovative solution is needed to achieve efficiency and consistency in the admission process at institutions. However, the existing research is lack of a simple practical method for informed decision-making for admissions. We develop a multi-criteria decision-making (MCDM) model to calculate the probability of success in course-based graduate studies in engineering. This approach integrates a wide range of quality indicators found in the existing literature. We hypothesise that the model will improve post-graduate admission decisions.A case study was conducted on students enrolled in the Master of Applied Science (MASc) in Oil and Gas Engineering programme at EnBeyond University. The results show no significant difference between the calculated chances of success and the obtained average. The proposed model is effective in predicting the chances of success. It will help to prioritise admission opportunities to those who have higher chances of success in graduate studies. It can also help to build a pre-assessment system with which prospective students can assess their admissibility before filing an application. This study is a first step towards a plethora of future research to come in this important area.